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bayesian inference

1904 papers

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Also known as

MCMC MBR BI BVMM MAP

Co-occurring keywords

variational inference (2069) markov chain monte carlo (724) gaussian process (1198) probabilistic modeling (851) uncertainty quantification (1365) posterior distribution (259) bayesian learning (185) gibbs sampling (201) graphical model (863) probabilistic model (476)

Papers

Probabilistic size-and-shape functional mixed models NIPS 2024
Constrained Sampling with Primal-Dual Langevin Monte Carlo NIPS 2024
Subsampling Error in Stochastic Gradient Langevin Diffusions AISTATS 2024
Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing NIPS 2024
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels AISTATS 2024
Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy NIPS 2024
Online Learning of Decision Trees with Thompson Sampling AISTATS 2024
A Framework for Improving the Reliability of Black-box Variational Inference JMLR 2024
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NIPS 2024
Sparse Variational Student-t Processes AAAI 2024
Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NIPS 2024
The Best of Both Worlds: On the Dilemma of Out-of-distribution Detection NIPS 2024
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models NIPS 2024
Score Operator Newton transport AISTATS 2024
Toward In-Context Teaching: Adapting Examples to Students’ Misconceptions ACL 2024
SEL-BALD: Deep Bayesian Active Learning with Selective Labels NIPS 2024
Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling JMLR 2024
Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling AAAI 2024
Spatial properties of Bayesian unsupervised trees COLT 2024
Estimating the Hallucination Rate of Generative AI NIPS 2024
Modeling Random Networks with Heterogeneous Reciprocity JMLR 2024
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning AISTATS 2024
Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity AISTATS 2024
Federated Label-Noise Learning with Local Diversity Product Regularization AAAI 2024
PAC-Bayes-Chernoff bounds for unbounded losses NIPS 2024